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benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines. With
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with expertise in the following four areas: (1) working with large-scale digital trace data; (2) building and running natural language processing and machine learning workflows; (3) experimental design
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, or the application of machine learning to registry data is highly valued. Experience in statistical analysis, including the use of statistical software such as STATA, R, Python, or SAS, will be viewed positively
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limited to machine learning, Natural Language Processing, large language models, data visualisations, and linked open data, can help streamline and improve editorial workflows. At the same time, it
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data. Develop and apply machine learning models to estimate uncertainty in climate impact statements. Analyse spatial and temporal patterns and trends in climate-extreme impacts. Cross-validate
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with expertise and experience in (1) Generative Modeling, (2) Multimodal Learning, (3) Generative AI and Computer Music, and (4) Efficient AI. Duties The appointees will be required to: (a) conduct
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data integration data quality data analytics programming languages (SQL, Python, Java) Complementary IT skills: machine learning image recognition sensor technologies robotic technologies
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: Development of machine learning algorithms for the localisation of seismic sources (e.g., on 2D grid maps) Analysis and preprocessing of large DAS datasets Use of synthetic training data from seismic
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sociology. Strong quantitative skills and experience with large-scale data analysis required. Computer Science/HCI: PhD in Computer Science, Human-Computer Interaction, Information Science, or related
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this diversity. Our research spans comparative genomics, chromatin architecture, gene expression, protein abundance, and metabolite profiling—combined with computational biology, machine learning, and advanced